Object Recognition Based on Local Steering Kernel and SVM
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 26، شماره: 11
سال انتشار: 1392
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 815
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شناسه ملی سند علمی:
JR_IJE-26-11_009
تاریخ نمایه سازی: 17 خرداد 1393
چکیده مقاله:
The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to beextracted where the variations occur in an image. To find the interest point, Wavelet based SalientPoint detector is used. Then, Local Steering Kernel is applied to the resultant pixels in order to obtain the most promising features. The features extracted will be over complete; so, in order to reduce dimensionality, Principal Component Analysis (PCA) is applied. Further, the sparse histogram is takenover the PCA output. The classifier used here is Support Vector Machine (SVM) Classifier. Bench mark database used is UIUC car database and the results obtained are satisfactory. The results obtained using LSK kernel is compared by varying parameters such as patch size, number of salientpoints/patches, smoothing parameter and scaling parameter
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نویسندگان
r AhilaPriyadharshini
Department of Electronics & Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India
s Arivazhagan
Department of Electronics & Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India